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The State of Go in 2026: What Changed In the Golang Ecosystem Since Last Year
What changed in the Go ecosystem since last year? We looked at the Developer Ecosystem 2026 survey to bring you the answers.
Nguồn: https://blog.jetbrains.com/go/2026/11/10/state-of-golang-2026. 8 Sync News chỉ tóm tắt và dẫn link; bản quyền nội dung thuộc tác giả và nguồn gốc.
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Show HN: A 15 MB self-hosted Netflix and Spotify for your media server
One self-hosted app for your shows, movies and music. - HolyArrs/HolyArrs
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Inside PGO
In the previous article , we made Go code faster by changing how it computes. SIMD lets one CPU instruction work on several values at once, and the simd/archsimd and simd packages give Go access to it. Our dot product ran about 9 times faster, but the code got a lot harder to read. At the end, I promised another route to speed, one where you don’t rewrite anything. That route is Profile-Guided Optimization (PGO). You record a CPU profile of where your program spends its time and give it back to the compiler, so it can work harder on the code that is actually hot. Your source stays exactly as it was. We briefly saw it in the IR post , and today we’re going deep into it.
Hacker News201 Hot2 phút
MCP Explained
An interactive guide to the Model Context Protocol: every JSON-RPC message on the wire, step by step. Transports, OAuth, tools, resources, sampling, elicitation, tasks, tool search and codemode.
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Amazon Bedrock AgentCore now offers a Web Search API
Discover more about what's new at AWS with Amazon Bedrock AgentCore now offers a Web Search API
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One flag, many guardrails: Making a platform safe enough to delegate
This post draws on a talk co-presented with Julien Semaan of Kubex at KubeCon + CloudNativeCon Europe 2026; GitOps Gone Wild: Hardening Delivery Pipelines for…
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The Next Web1 Hot4 phút
Australia plans AI safety regulator after OpenAI agent breach
Australia will create an AI safety regulator and require AI companies to report hacks, after an OpenAI agent accessed a Medicare data portal.
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Red Flags to Watch for When Choosing Between AI Pentesting Vendors
Choosing between AI pentesting vendors requires looking past marketing labels like 'autonomous' or 'agentic' because the underlying systems vary widely. A Stanford-led study ran different AI agent frameworks against a live 8,000-host network and found that between 55% and 82% of reported findings were confirmed as real vulnerabilities. Swapping only the underlying model moved one framework's valid finding rate from 57% to 80%, yet that same framework still scored lowest overall since its findings stayed shallow. On a CTF-style benchmark two frameworks scored near-identically (48.6% vs 45.9%), but on the live network one scored nearly three times higher on severity and complexity. Buyers should demand proof of exploitation, real-network results, clear safety controls, data handling answers and clarity on what 'continuous' actually means.
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